Machine Learning and Artificial Intelligence

Machine Learning

Artificial Intelligence

USE AI AND ML TO DRIVE BETTER DECISION-MAKING AND INNOVATE EXPERIENCES

AWS Machine Learning (ML) is a machine service that allows you to easily build predictive applications, including fraud detection, demand forecasting, and click prediction. Using powerful algorithms that can help you create machine learning models by finding patterns in existing data, AWS Machine Learning utilizes these patterns to make predictions from new data as it becomes available. AWS Machine Learning is highly scalable, optimized ML/AI high-performance compute, and no compromises on security and analytics

WHAT IS THE DIFFERENCE BETWEEN ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND DEEP LEARNING?

USING AWS AI SERVICES TO ADD INTELLIGENCE TO YOUR APPLICATIONS AND WORKFLOWS

AWS AI Services and AWS Platform services NorthBay uses:

Recommendations

Personalize experiences for your customers with the same recommendation technology used at Amazon.com such as Amazon PERSONALIZE

Forecasting

Build accurate forecasting models based on the same machine learning forecasting technology used by Amazon.com such as Amazon FORECAST

Transcription

From analytics tools with conversational agents to providing Amazon-like personalized recommendations, NorthBay has used these innovative AI services to boost enterprise applications.

AWS SERVICES

Build, train and deploy Machine Learning models at any scale

AI AND ML ENABLED USE CASES NORTHBAY HAS SUPPORTED CUSTOMERS WITH

NorthBay has helped customers in dozens of industries leverage their data
stored in AWS to test and implement numerous use cases including:

FRAUD DETECTION

PREDICTIVE ANALYTICS

PRODUCTION SHORTAGES

SALES RECOMMENDATIONS

SALES PATTERN RECOGNITION

DOCUMENT CLASSIFICATION

PERSONALIZED MARKETING

CUSTOMER CHURN PREDICTIONS

CUSTOMER SUPPORT

EDUCATION/LEARNING INTERVENTION

STUDENT LEARNING PATTERNS

EQUIPMENT MAINTENANCE PREVENTION (SAFETY, REPAIRS, ETC.)

OUR AI AND ML PARTNERSHIP WITH AWS

NorthBay’s unique partnership with AWS has enabled us to develop a consistent methodology of formulating an implementation methodology that has been proven to be highly successful and efficient.

NORTHBAY’S ML / AI IMPLEMENTATION METHODOLOGY

Machine learning (ML) can help you use historical data to make better business decisions. ML algorithms discover patterns in data and construct predictive models using these patterns, allowing you to use the models to make predictions on future data. For example, one possible application of ML would be to predict whether or not a customer will purchase a particular product based on past behavior and use this prediction to send a personalized promotional email to that customer.

Amazon Machine Learning APIs and wizards make it easy for any developer to create and fine-tune ML models from data stored in Amazon S3, Amazon Redshift, or MySQL databases in Amazon RDS, and query these models for predictions.

From Models to Predictions in Seconds

Amazon Machine Learning is a managed service that provides end-to-end model creation, deployment, and monitoring. Once your model is ready, you can quickly and reliably generate predictions for your applications, eliminating the time and investment needed to build, scale, and maintain machine learning infrastructure.

Scalable, High Performance Prediction Generation Service

Amazon Machine Learning prediction APIs can be used to generate billions of predictions for your applications. You can request predictions for large numbers of data records all at once using the batch prediction API or use the real-time API to obtain predictions for individual data records, and use them within the interactive web, mobile, or desktop applications.

Low Cost and Efficient

With Amazon Machine Learning there is no setup cost and you pay as you go, so you can start small and scale as your application grows.

Leverage Proven Technology

Amazon Machine Learning is based on the same proven, highly scalable, ML technology used by Amazon to perform critical functions like supply chain management, fraudulent transaction identification, and catalog organization.

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